Zero-safe nets: comparing the collective and individual token approaches
Information and Computation - Special issue on EXPRESS 1997
Genetic process mining: an experimental evaluation
Data Mining and Knowledge Discovery
Rediscovering workflow models from event-based data using little thumb
Integrated Computer-Aided Engineering
Process Discovery using Integer Linear Programming
Fundamenta Informaticae - Petri Nets 2008
Fuzzy mining: adaptive process simplification based on multi-perspective metrics
BPM'07 Proceedings of the 5th international conference on Business process management
Soundness of workflow nets: classification, decidability, and analysis
Formal Aspects of Computing
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
An SMT-Based discovery algorithm for c-nets
PETRI NETS'12 Proceedings of the 33rd international conference on Application and Theory of Petri Nets
Simplifying discovered process models in a controlled manner
Information Systems
Amending C-net discovery algorithms
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Process discovery--discovering a process model from example behavior recorded in an event log--is one of the most challenging tasks in process mining. The primary reason is that conventional modeling languages (e.g., Petri nets, BPMN, EPCs, and ULM ADs) have difficulties representing the observed behavior properly and/or succinctly. Moreover, discovered process models tend to have deadlocks and livelocks. Therefore, we advocate a new representation more suitable for process discovery: causal nets. Causal nets are related to the representations used by several process discovery techniques (e.g., heuristic mining, fuzzy mining, and genetic mining). However, unlike existing approaches, we provide declarative semantics more suitable for process mining. To clarify these semantics and to illustrate the non-local nature of this new representation, we relate causal nets to Petri nets.